Combining Alphas via Bounded Regression
AbstractWe give an explicit algorithm and source code for combining alpha streams via bounded regression. In practical applications, typically, there is insufficient history to compute a sample covariance matrix (SCM) for a large number of alphas. To compute alpha allocation weights, one then resorts to (weighted) regression over SCM principal components. Regression often produces alpha weights with insufficient diversification and/or skewed distribution against, e.g., turnover. This can be rectified by imposing bounds on alpha weights within the regression procedure. Bounded regression can also be applied to stock and other asset portfolio construction. We discuss illustrative examples. View Full-Text
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Kakushadze, Z. Combining Alphas via Bounded Regression. Risks 2015, 3, 474-490.
Kakushadze Z. Combining Alphas via Bounded Regression. Risks. 2015; 3(4):474-490.Chicago/Turabian Style
Kakushadze, Zura. 2015. "Combining Alphas via Bounded Regression." Risks 3, no. 4: 474-490.